{"id":"W3186877078","doi":"10.3390/jpm11080736","title":"Of Screening, Stratification, and Scores","year":2021,"lang":"en","type":"review","venue":"Journal of Personalized Medicine","topic":"Global Cancer Incidence and Screening","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Genome Canada","keywords":"Risk stratification; Population stratification; Risk assessment; Stratification (seeds); Health care; Actuarial science; Risk analysis (engineering); Medicine; Environmental health; Computer science; Business; Economics; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001069143,0.0002796985,0.003238812,0.0003545634,0.00003666836,0.000009933116,0.0001532751,0.0001993185,0.0005629854],"category_scores_gemma":[0.001045365,0.0001751832,0.0004883373,0.0004161366,0.0003790799,0.00008395626,0.00002936096,0.0005817087,7.346442e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007308321,"about_ca_system_score_gemma":0.0009601119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003316288,"about_ca_topic_score_gemma":0.000003064238,"domain_scores_codex":[0.9970917,0.0001317667,0.001470734,0.0002085532,0.0009232485,0.0001739855],"domain_scores_gemma":[0.9965577,0.0002450619,0.001779085,0.0002316438,0.0008957759,0.0002907496],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001259476,0.00005142976,0.0002408659,0.01433344,0.000921534,0.0004917791,0.000453911,1.670806e-7,0.00005177071,0.0008943405,0.01450305,0.9679317],"study_design_scores_gemma":[0.001449999,0.0007592132,0.0001101967,0.1107946,0.004505103,0.005232307,0.000699492,0.000002306088,0.000005041439,0.00002637695,0.8762971,0.0001183084],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006936252,0.997764,0.0004726231,0.0007310313,0.000184651,0.0002240032,0.000008967459,0.000004665203,0.0005407265],"genre_scores_gemma":[0.00007989258,0.99426,0.003925408,0.0001869022,0.0009237792,0.000003215696,0.00003426672,0.00002523601,0.000561329],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9678134,"threshold_uncertainty_score":0.7143763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2146322150358664,"score_gpt":0.450312127934288,"score_spread":0.2356799128984216,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}